Media & EntertainmentResearch & Development

How Luminate Processes 3.5TB of Entertainment Data 334% Faster with Snowflake

Luminate powers the Billboard music charts and provides data intelligence across music, film, and television for major record labels, studios, and talent agencies. After migrating from on-premises Spark and SQL Server to Snowflake, the company achieved 334% faster daily data processing across more than 3.5 terabytes of daily input. Market reports that previously took a full month now run overnight, and Luminate can for the first time deliver cross-industry insights correlating music and TV consumption.

Outcomes

334%Increase in daily data processing speed
3.5TB+Daily data volume processed
OvernightMarket report turnaround time

Tools & Technologies

1S
Snowflake
Cloud data warehouse by Snowflake for storing, querying, and sharing structured and semi-structured data.
2SC
Snowflake Cortex AI
Built-in AI and ML capabilities within the Snowflake Data Cloud

AI Categories

Challenge

Legacy on-premises infrastructure could not process 3.5TB of daily entertainment data fast enough, forcing market reports to take a full month to complete and preventing cross-industry analysis between music and TV consumption datasets.

Solution

Luminate migrated to Snowflake as the core data lake, using Snowflake Secure Data Sharing for near-real-time client delivery, Snowpark ML for Python-based modeling, and independent storage/compute scaling to accelerate all data processing pipelines.

Full Story

Every song streamed, every episode watched — Luminate captures it and turns raw playback data into the authoritative charts and market intelligence that drive royalties, awards, and industry strategy. With hundreds of verified sources feeding more than 3.5 terabytes of data daily, the company’s ability to deliver timely, accurate insights is not just a product differentiator; it defines its credibility with record labels, studios, and streaming platforms worldwide.

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Source

SNOWFLAKE
April 2026
Original case study

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